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Views not necessarily those of the U. S. Energy Information Administration. Staff papers presented here are preliminary materials circulated to stimulate discussion and critical comment. The analysis and conclusions set forth are those of the authors and do not indicate concurrence by the U. S. Energy Information Administration. References in publications (other than acknowledgment) should be cleared with the author(s) to protect the tentative character of these papers.

Update to Industrial drivers in the AEO2015 as a result of new input-output dataThis paper will discuss major methodological changes for macroeconomic modeling of the industrial sector from the AEO2014 to the AEO2015, highlighting how industrial sector output (agriculture, mining, construction, and manufacturing) and explanatory GDP components, also called final demand categories, affect the projection of industrial output. It will focus on how BEA's IO table updates, combined with greater use of available data, have changed the relationship between final demand and supply chain requirements and industry output across various aggregates of the industrial sector.released: May 4, 2015; contact author(s):Elizabeth Sendich

Natural Gas and U.S. Industrial Production: A Closer Look at Four IndustriesWe consider the relationship between natural gas prices and production in the U.S. resins, agricultural
chemicals, cement, and aluminium industries. Overall, our analysis using various tests and regressions
does not allow for generalizations about the association between natural gas prices and production
across these four energy-intensive industries. Rather, the relationships between natural gas and
production appear to be driven by the particular institutional details of each industry.

The Importance of Natural Gas in the Industrial Sector With a Focus on Energy-Intensive IndustriesThe industrial sector, which is comprised of manufacturing, construction, agriculture, and mining industries, is one of the largest consumers of natural gas (NG), and increased energy production is known to result in more economic activity broadly. The industrial sector consumes approximately one-third of total U.S. dry natural gas and natural gas liquids as feedstock, and it may be an important beneficiary of an expansion in oil and gas resources. Studies show that some expected links between aggregate industrial production, energy, and economic indicators may not be as clear as once thought. This work aims to build on previous work using statistical tools to determine if simple, long-term relationships between NG price and supply and industrial production exist and have ever changed or are currently changing to determine if past data can inform estimations of future trends.

Energy Production and Trade: An Overview of Some Macroeconomic IssuesLarge increases in American oil and gas production have opened a debate about relaxing export restrictions on crude oil and natural gas. Unfortunately, many of the approaches used to defend opposing positions can be difficult to understand and follow. This paper attempts to review, outline, and clarify some of the key points associated with trade theory, evidence, and data as they relate to energy exports and macroeconomics. The goal is to sketch a framework for thinking about energy production and trade that fits with standard macroeconomic theory, both in international trade and international finance.

Electricity Use as an Indicator of U.S. Economic ActivityWe argue for the resurrection of an old idea: electricity use as an indicator of U.S. economic activity. Our analysis relies on associations–the 40-year correlation between growth rates in real GDP and electricity use can be as high as 89% –and intuition. Electricity use and economic conditions should move together. The vast majority of goods and services are still produced using electricity; services may require less electricity, but they still require some. Electricity use also has other strengths –it is broad-based and the data are available weekly, possibly hourly by 2015.

Alternative Measures of Welfare in Macroeconomic ModelsThe impacts and costs and benefits of different policies and scenarios can be calculated in several different ways. The measure chosen often depends on the class of model employed and the purposes of the policy and/or study. The sum total of costs and benefits, or changes in costs and benefits, is termed welfare. Traditionally, EIA has used measures such as GDP, consumption, and unemployment (among others) as ways to describe the overall economic impacts of policies, mainly highlighting changes in consumption as a proxy for welfare. Using a variety of different measures of welfare to evaluate policy changes is desirable. This is particularly true in the case of utility, which is unique because it can incorporate the direct and indirect costs and benefits of different policies. Given the assumptions and complications required to make welfare calculations using the current NEMS setup, using a CGE model to make such calculations is a good option.

An Evaluation of Macroeconomic Models for use at EIAEIA has traditionally used macroeconomic models to produce forecasts and to evaluate the impact of different government policies. This document reviews the current EIA approach and alternatives from a methodological perspective. It begins with a short summary of different macroeconomic models and their strengths and weaknesses when used for policy analysis and in producing forecasts. This is followed by recommendations for possible use at EIA based on the capabilities of each model type. The mechanics of each specific macroeconomic model are reviewed next, along with additional details on policy analysis and forecasting. The final section is a technical appendix with the relevant mathematical detail on each model.

Comparison of International Energy Intensities across the G7 and other parts of Europe, include UkraineConsistent data are critical for comparisons of energy consumption across diverse nations. This document uses estimates done by EIA for the energy intensity of Ukraine, the representatives of the Group of Seven (G7), and other parts of Europe. Values are provided for the national economy, the industrial sector, and a small selection of industries. Some of the key drivers for the results are: the natural resources and landscape, the nation's approach to efficiency, the age of the capital stock, the bundle of products being produced, and production processes and technologies. This paper compares energy intensity in 2011 and suggests possible explanations for country differences for possible future research topics. This is not intended to be an exhaustive inter-country analysis of energy use and provides a contrast to other country intensity analysis[1] because the estimates are nominal values for a single year using market exchange rates for GDP.

Global Natural Gas Overview: A Report Prepared by Leidos, Inc., Under Contract to EIAThe attached report, prepared by Leidos, Inc., under contract to EIA, provides a broad overview of
today's global natural gas markets, possible drivers of the evolution of the global gas market, and a high
level overview of select economic theories that may be applied to describe basic market interactions in
current and future global natural gas markets.released: August 26, 2014; contact author(s):Angelina LaRose

WELLS AND DRILLING

Improving Well Productivity Based Modeling with the Incorporation of Geologic DependiciesThe U.S. Energy Information Administration (EIA) utilizes supply-side modeling of well-level performance measures quantified at the county level for resource plays. Well performance, however, does not depend upon political boundaries. Aligning well-productivity with underlying geologic dependencies will improve production projections by better quantifying the area, and the well-performance in that area, of potential future development.

The choice of geologic dependencies can be as flexible and numerous as time and resources permit, or a derivative product of multiple dependencies. The summation of the well-performance and area is also a reasonable method to estimate an amount of resource that might be recoverable under a given set of technological and economic conditions.

Quantifying Drilling EfficiencyThis paper examines the methods used to measure drilling efficiency and the difficulties encountered when using various data sources. The analysis exames the technologies used before, during, and after rotary rig iperation which shape overall productivity results.

The Information Role of Spot Prices and InventoriesUsing a rational expectations approach, we show why and how differences in beliefs, as well as the volume of speculative futures trading, may vary across commodities and through time. We demonstrate that equilibrium differences in beliefs are determined by characteristics of the underlying commodity, including storage costs, the amplitude of shocks, the accuracy of information available to informed investors, the numbers of informed and uninformed traders, and the elasticity of demand and supply. We also demonstrate that passive investors magnify equilibrium differences in beliefs and expand the scope for financial speculation--even though they do not themselves speculate. Finally, we argue that fundamental determinants of speculative futures trading may have been misinterpreted by some as "excessive" speculation in the energy markets in recent years.

Are there Gains from Pooling Real-Time Oil Price Forecasts?The answer depends on the objective. The approach of combining five of the leading forecasting models with equal weights dominates the strategy of selecting one model and using it for all horizons up to two years. Even more accurate forecasts, however, are obtained when allowing the forecast combinations to vary across forecast horizons. While the latter approach is not always more accurate than selecting the single most accurate forecasting model by horizon, its accuracy can be shown to be much more stable over time. The MSPE of real-time pooled forecasts is between 3% and 29% lower than that of the no-change forecast and its directional accuracy as high as 73%. Our results are robust to alternative oil price measures and apply to monthly as well as quarterly forecasts. We illustrate how forecast pooling may be used to produce real-time forecasts of the real and the nominal price of oil in a format consistent with that employed by the U.S. Energy Information Administration in releasing its short-term oil price forecasts and we compare these forecasts during key historical episodes.

Contango in Cushing? Evidence on Financial-Physical Interactions in the U.S. Crude Oil MarketWhile there has been considerable focus, especially in the aftermath of the 2007-08 oil price spike, on the role of financial speculators in influencing oil prices, a question that lies at the heart of this debate -- how oil futures trading is related to spot oil prices — remains unresolved. A financial speculator who expects future oil prices to rise and wants to take a speculative position based on this expectation would typically go long in financial futures contracts. An index investor who wants to invest in oil will take a similar long position in futures contracts, which would be rolled over periodically. If such speculative or investment activity increases the futures price sufficiently relative to the prevailing spot price, a rational market response would be for arbitrageurs to step in to buy oil in the spot market and store it while simultaneously selling futures.

Implications of Changing Correlations Between WTI and Other Commodities, Asset Classes, and Implied VolatilityCrude oil price movements are constantly changing as the market reacts to new information regarding current production, consumption and inventory levels of crude oil and petroleum products. Oil prices are also affected by changes in the market’s expectations of the future supply and demand balance. Depending on market conditions and sentiment, different time periods can have news and events related to either supply or demand issues as the dominant factors dictating price movements. The analysis presented here attempts to identify time periods when crude oil prices are responding more to either supply or demand, relative to the other, by examining the magnitude and sign of the correlation of crude oil prices against other commodities and asset classes.

Factors Influencing Oil Prices: A Survey of the Current State of Knowledge in the Context of the 2007-08 Oil Price VolatilityThe current state of knowledge on the important factors influencing oil prices have been identified in relevant venues, including recent academic literature, government reports, policy debate, and industry analysis. In this paper, we briefly survey the current state of knowledge on this topic, based on an objective assessment of each factor's influence and potential to influence ongoing policy debates, or academic or industry research. In sections 2 to 6, we provide a summary of what current research tells us, and with what degree of confidence, about the identified factors, their interactions, and influences on prices. We draw on nearly 200 research papers, articles, and industry and policy documents, mostly work published in the past five years. Section 7 concludes.

Issues and Methods for Estimating the Share of Ethanol in the Motor Gasoline SupplyThis paper describes publicly available fuel ethanol data and suggests methodologies to estimate the percentage of ethanol used in the United States gasoline supply. These methods, which use historical U.S. Energy Information Administration (EIA) survey data and information from other sources, involve calculations based on motor gasoline and ethanol production, net imports, and inputs into refineries and blenders.